change ui add 3d show

app.py

@@ -1,11 +1,11 @@
 # main.py
 # 主入口文件，负责启动 Gradio UI
 import gradio as gr
-from config import SCENE_CONFIGS, MODEL_CHOICES, MODE_CHOICES
+from config import SCENE_CONFIGS, MODEL_CHOICES, MODE_CHOICES, EPISODE_CONFIGS
 from backend_api import submit_to_backend, get_task_status, get_task_result
 from logging_utils import log_access, log_submission, is_request_allowed
 from simulation import stream_simulation_results, convert_to_h264, create_final_video_from_oss_images
-from ui_components import update_history_display, update_scene_display, update_log_display, get_scene_instruction
+from ui_components import update_history_display, update_scene_display, update_episode_display, update_log_display, get_scene_instruction
 from oss_utils import download_oss_file, get_user_tmp_dir, cleanup_user_tmp_dir, oss_file_exists, clean_oss_result_path
 import os
 from datetime import datetime
@@ -136,6 +136,12 @@ custom_css = """
 .history-accordion {
     margin-bottom: 10px;
 }
+.scene-preview {
+    height: 400px;
+    border: 1px solid #ddd;
+    border-radius: 8px;
+    overflow: hidden;
+}
 """
 
 header_html = """
@@ -174,18 +180,29 @@ with gr.Blocks(title="InternNav Model Inference Demo", css=custom_css) as demo:
     with gr.Row():
         with gr.Column(elem_id="simulation-panel"):
             gr.Markdown("### Simulation Settings")
-            scene_dropdown = gr.Dropdown(
-                label="Choose a scene",
-                choices=list(SCENE_CONFIGS.keys()),
-                value="demo1",
-                interactive=True
-            )
-            scene_description = gr.Markdown("")
-            scene_preview = gr.Image(
-                label="Scene Preview",
-                elem_classes=["scene-preview"],
-                interactive=False
-            )
+            with gr.Row():
+                scene_dropdown = gr.Dropdown(
+                    label="Choose a scene",
+                    choices=list(SCENE_CONFIGS.keys()),
+                    value="demo1",
+                    interactive=True
+                )
+                episode_dropdown = gr.Dropdown(
+                    label="Select Start Position",
+                    choices=list(EPISODE_CONFIGS.keys()),
+                    value="episode_1",
+                    interactive=True
+                )
+            
+            with gr.Row():
+                scene_preview = gr.Model3D(
+                    elem_classes=["scene-preview"],
+                    camera_position=(90.0, 120, 20000.0)
+                )
+                fps_preview = gr.Image(label="FPS Preview")
+            
+            scene_description = gr.Markdown("### Scene preview")
+            
             prompt_input = gr.Textbox(
                 label="Navigation Prompt",
                 value="Walk past the left side of the bed and stop in the doorway.",
@@ -209,6 +226,16 @@ with gr.Blocks(title="InternNav Model Inference Demo", css=custom_css) as demo:
                 fn=lambda scene: [update_scene_display(scene)[0], update_scene_display(scene)[1], get_scene_instruction(scene)],
                 inputs=scene_dropdown,
                 outputs=[scene_description, scene_preview, prompt_input]
+            ).then(
+                update_episode_display,
+                inputs=[scene_dropdown, episode_dropdown],
+                outputs=[fps_preview]
+            )
+            
+            episode_dropdown.change(
+                update_episode_display,
+                inputs=[scene_dropdown, episode_dropdown],
+                outputs=[fps_preview]
             )
             
             submit_btn = gr.Button("Start Navigation Simulation", variant="primary")
@@ -257,6 +284,9 @@ with gr.Blocks(title="InternNav Model Inference Demo", css=custom_css) as demo:
     demo.load(
         fn=lambda: update_scene_display("demo1"),
         outputs=[scene_description, scene_preview]
+    ).then(
+        fn=lambda: update_episode_display("demo1", "episode_1"),
+        outputs=[fps_preview]
     )
     demo.load(
         fn=record_access,

app_old.py

@@ -0,0 +1,277 @@
+# main.py
+# 主入口文件，负责启动 Gradio UI
+import gradio as gr
+from config import SCENE_CONFIGS, MODEL_CHOICES, MODE_CHOICES
+from backend_api import submit_to_backend, get_task_status, get_task_result
+from logging_utils import log_access, log_submission, is_request_allowed
+from simulation import stream_simulation_results, convert_to_h264, create_final_video_from_oss_images
+from ui_components import update_history_display, update_scene_display, update_log_display, get_scene_instruction
+from oss_utils import download_oss_file, get_user_tmp_dir, cleanup_user_tmp_dir, oss_file_exists, clean_oss_result_path
+import os
+from datetime import datetime
+
+SESSION_TASKS = {}
+
+def run_simulation(scene, model, mode, prompt, history, request: gr.Request):
+    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    scene_desc = SCENE_CONFIGS.get(scene, {}).get("description", scene)
+    user_ip = request.client.host if request else "unknown"
+    session_id = request.session_hash
+    
+    if not is_request_allowed(user_ip):
+        log_submission(scene, prompt, model, user_ip, "IP blocked temporarily")
+        raise gr.Error("Too many requests from this IP. Please wait and try again one minute later.")
+    
+    # 提交任务到后端
+    submission_result = submit_to_backend(scene, prompt, mode, model, user_ip)
+    if submission_result.get("status") != "pending":
+        log_submission(scene, prompt, model, user_ip, "Submission failed")
+        raise gr.Error(f"Submission failed: {submission_result.get('message', 'unknown issue')}")
+    
+    try:
+        task_id = submission_result["task_id"]
+        SESSION_TASKS[session_id] = task_id
+        gr.Info(f"Simulation started, task_id: {task_id}")
+        
+        import time
+        time.sleep(5)
+        status = get_task_status(task_id)
+        # OSS上的结果文件夹路径，不再检查本地路径是否存在
+        result_folder = clean_oss_result_path(status.get("result", f"gradio_demo/tasks/{task_id}"), task_id)
+        
+    except Exception as e:
+        log_submission(scene, prompt, model, user_ip, str(e))
+        raise gr.Error(f"error occurred when parsing submission result from backend: {str(e)}")
+
+    # 流式输出视频片段（从OSS读取）
+    try:
+        for video_path in stream_simulation_results(result_folder, task_id, request):
+            if video_path:
+                yield video_path, history
+    except Exception as e:
+        log_submission(scene, prompt, model, user_ip, str(e))
+        raise gr.Error(f"流式输出过程中出错: {str(e)}")
+
+    # 获取最终任务状态
+    status = get_task_status(task_id)
+    if status.get("status") == "completed":
+        try:
+            # 从OSS上的所有图片拼接成最终视频（6帧每秒）
+            gr.Info("Creating final video from all OSS images...")
+            video_path = create_final_video_from_oss_images(result_folder, task_id, request, fps=6)
+            gr.Info(f"Final video created successfully with 6 fps!")
+                
+        except Exception as e:
+            print(f"Error creating final video from OSS images: {e}")
+            log_submission(scene, prompt, model, user_ip, f"Final video creation failed: {str(e)}")
+            video_path = None
+        new_entry = {
+            "timestamp": timestamp,
+            "scene": scene,
+            "model": model,
+            "mode": mode,
+            "prompt": prompt,
+            "video_path": video_path
+        }
+        updated_history = history + [new_entry]
+        if len(updated_history) > 10:
+            updated_history = updated_history[:10]
+        log_submission(scene, prompt, model, user_ip, "success")
+        gr.Info("Simulation completed successfully!")
+        yield None, updated_history
+    elif status.get("status") == "failed":
+        log_submission(scene, prompt, model, user_ip, status.get('result', 'backend error'))
+        raise gr.Error(f"任务执行失败: {status.get('result', 'backend 未知错误')}")
+        yield None, history
+    elif status.get("status") == "terminated":
+        log_submission(scene, prompt, model, user_ip, "terminated")
+        # 对于终止的任务，不再检查本地文件
+        yield None, history
+    else:
+        log_submission(scene, prompt, model, user_ip, "missing task's status from backend")
+        raise gr.Error("missing task's status from backend")
+        yield None, history
+
+def cleanup_session(request: gr.Request):
+    session_id = request.session_hash
+    task_id = SESSION_TASKS.pop(session_id, None)
+    from config import BACKEND_URL
+    import requests
+    if task_id:
+        try:
+            requests.post(f"{BACKEND_URL}/predict/terminate/{task_id}", timeout=3)
+        except Exception:
+            pass
+    
+    # 清理用户临时目录
+    cleanup_user_tmp_dir(session_id)
+
+def record_access(request: gr.Request):
+    user_ip = request.client.host if request else "unknown"
+    user_agent = request.headers.get("user-agent", "unknown")
+    log_access(user_ip, user_agent)
+    return update_log_display()
+
+
+
+custom_css = """
+#simulation-panel {
+    border-radius: 8px;
+    padding: 20px;
+    background: #f9f9f9;
+    box-shadow: 0 2px 4px rgba(0,0,0,0.1);
+}
+#result-panel {
+    border-radius: 8px;
+    padding: 20px;
+    background: #f0f8ff;
+}
+.dark #simulation-panel { background: #2a2a2a; }
+.dark #result-panel { background: #1a2a3a; }
+.history-container {
+    max-height: 600px;
+    overflow-y: auto;
+    margin-top: 20px;
+}
+.history-accordion {
+    margin-bottom: 10px;
+}
+"""
+
+header_html = """
+<div style="display: flex; justify-content: space-between; align-items: center; width: 100%; margin-bottom: 20px; padding: 20px; background: linear-gradient(135deg, #e0e5ec 0%, #a7b5d0 100%); border-radius: 8px; box-shadow: 0 2px 8px rgba(0,0,0,0.1);">
+    <div style="display: flex; align-items: center;">
+        <img src="https://www.shlab.org.cn/static/img/index_14.685f6559.png" alt="Institution Logo" style="height: 60px; margin-right: 20px;">
+        <div>
+            <h1 style="margin: 0; color: #2c3e50; font-weight: 600;">🤖 InternNav Model Inference Demo</h1>
+            <p style="margin: 4px 0 0 0; color: #5d6d7e; font-size: 0.9em;">Model trained on InternNav framework</p>
+        </div>
+    </div>
+    <div style="display: flex; gap: 15px; align-items: center;">
+        <a href="https://github.com/OpenRobotLab" target="_blank" style="text-decoration: none; transition: transform 0.2s;" onmouseover="this.style.transform='scale(1.1)'" onmouseout="this.style.transform='scale(1)'">
+            <img src="https://github.githubassets.com/images/modules/logos_page/GitHub-Mark.png" alt="GitHub" style="height: 30px;">
+        </a>
+        <a href="https://huggingface.co/OpenRobotLab" target="_blank" style="text-decoration: none; transition: transform 0.2s;" onmouseover="this.style.transform='scale(1.1)'" onmouseout="this.style.transform='scale(1)'">
+            <img src="https://huggingface.co/front/assets/huggingface_logo-noborder.svg" alt="HuggingFace" style="height: 30px;">
+        </a>
+        <a href="https://huggingface.co/spaces/OpenRobotLab/InternManip-eval-demo" target="_blank">
+            <button style="padding: 8px 15px; background: #3498db; color: white; border: none; border-radius: 4px; cursor: pointer; font-weight: 500; transition: all 0.2s;" 
+                    onmouseover="this.style.backgroundColor='#2980b9'; this.style.transform='scale(1.05)'" 
+                    onmouseout="this.style.backgroundColor='#3498db'; this.style.transform='scale(1)'">
+                Go to InternManip Demo
+            </button>
+        </a>
+    </div>
+</div>
+"""
+
+
+
+with gr.Blocks(title="InternNav Model Inference Demo", css=custom_css) as demo:
+    gr.HTML(header_html)
+    
+    history_state = gr.State([])
+    with gr.Row():
+        with gr.Column(elem_id="simulation-panel"):
+            gr.Markdown("### Simulation Settings")
+            scene_dropdown = gr.Dropdown(
+                label="Choose a scene",
+                choices=list(SCENE_CONFIGS.keys()),
+                value="demo1",
+                interactive=True
+            )
+            scene_description = gr.Markdown("")
+            scene_preview = gr.Image(
+                label="Scene Preview",
+                elem_classes=["scene-preview"],
+                interactive=False
+            )
+            prompt_input = gr.Textbox(
+                label="Navigation Prompt",
+                value="Walk past the left side of the bed and stop in the doorway.",
+                placeholder="e.g.: 'Walk past the left side of the bed and stop in the doorway.'",
+                lines=2,
+                max_lines=4
+            )
+            model_dropdown = gr.Dropdown(
+                label="Chose a pretrained model",
+                choices=MODEL_CHOICES,
+                value=MODEL_CHOICES[0],
+                interactive=True
+            )
+            mode_dropdown = gr.Dropdown(
+                label="Select Mode",
+                choices=MODE_CHOICES,
+                value=MODE_CHOICES[0],
+                interactive=True
+            )
+            scene_dropdown.change(
+                fn=lambda scene: [update_scene_display(scene)[0], update_scene_display(scene)[1], get_scene_instruction(scene)],
+                inputs=scene_dropdown,
+                outputs=[scene_description, scene_preview, prompt_input]
+            )
+            
+            submit_btn = gr.Button("Start Navigation Simulation", variant="primary")
+        with gr.Column(elem_id="result-panel"):
+            gr.Markdown("### Latest Simulation Result")
+            video_output = gr.Video(
+                label="Live",
+                interactive=False,
+                format="mp4",
+                autoplay=True,
+                streaming=True
+            )
+            with gr.Column() as history_container:
+                gr.Markdown("### History")
+                gr.Markdown("#### History will be reset after refresh")
+                history_slots = []
+                for i in range(10):
+                    with gr.Column(visible=False) as slot:
+                        with gr.Accordion(visible=False, open=False) as accordion:
+                            video = gr.Video(interactive=False)
+                            detail_md = gr.Markdown()
+                    history_slots.append((slot, accordion, video, detail_md))
+    gr.Examples(
+        examples=[
+            ["demo1", "rdp", "vlnPE", "Walk past the left side of the bed and stop in the doorway."],
+            ["demo2", "rdp", "vlnPE", "Walk through the bathroom, past the sink and toilet. Stop in front of the counter with the two suitcase."],
+            ["demo3", "rdp", "vlnPE", "Do a U-turn. Walk forward through the kitchen, heading to the black door. Walk out of the door and take a right onto the deck. Walk out on to the deck and stop."],
+            ["demo4", "rdp", "vlnPE", "Walk out of bathroom and stand on white bath mat."],
+            ["demo5", "rdp", "vlnPE", "Walk straight through the double wood doors, follow the red carpet straight to the next doorway and stop where the carpet splits off."]
+        ],
+        inputs=[scene_dropdown, model_dropdown, mode_dropdown, prompt_input],
+        label="Navigation Task Examples"
+    )
+    submit_btn.click(
+        fn=run_simulation,
+        inputs=[scene_dropdown, model_dropdown, mode_dropdown, prompt_input, history_state],
+        outputs=[video_output, history_state],
+        queue=True,
+        api_name="run_simulation"
+    ).then(
+        fn=update_history_display,
+        inputs=history_state,
+        outputs=[comp for slot in history_slots for comp in slot],
+        queue=True
+    )
+    demo.load(
+        fn=lambda: update_scene_display("demo1"),
+        outputs=[scene_description, scene_preview]
+    )
+    demo.load(
+        fn=record_access,
+        inputs=None,
+        outputs=None,
+        queue=False
+    )
+    demo.queue(default_concurrency_limit=8)
+    demo.unload(fn=cleanup_session)
+
+if __name__ == "__main__":
+    demo.launch(
+        server_name="0.0.0.0", 
+        server_port=7860,  # Hugging Face Space默认端口
+        share=False, 
+        debug=False,  # 生产环境建议关闭debug
+        allowed_paths=["./assets", "./logs", "./tmp"]  # 添加临时目录到允许路径
+    )

config.py

@@ -14,33 +14,53 @@ SCENE_CONFIGS = {
         "description": "Demo 1",
         "objects": ["bedroom", "kitchen", "living room", ""],
         "preview_image": "./assets/scene_1.png",
+        "glb_path": "scene_assets/demo1_no_ceiling.glb",
         "default_instruction": "Walk past the left side of the bed and stop in the doorway."
     },
     "demo2": {
         "description": "Demo 2",
         "objects": ["office", "meeting room", "corridor"],
         "preview_image": "./assets/scene_2.png",
+        "glb_path": "scene_assets/demo2_no_ceiling.glb",
         "default_instruction": "Walk through the bathroom, past the sink and toilet. Stop in front of the counter with the two suitcase."
     },
     "demo3": {
         "description": "Demo 3",
         "objects": ["garage", "workshop", "storage"],
         "preview_image": "./assets/scene_3.png",
+        "glb_path": "scene_assets/demo3_no_ceiling.glb",
         "default_instruction": "Do a U-turn. Walk forward through the kitchen, heading to the black door. Walk out of the door and take a right onto the deck. Walk out on to the deck and stop."
     },
     "demo4": {
         "description": "Demo 4",
         "objects": ["garden", "patio", "pool"],
         "preview_image": "./assets/scene_4.png",
+        "glb_path": "scene_assets/demo4_no_ceiling.glb",
         "default_instruction": "Walk out of bathroom and stand on white bath mat."
     },
     "demo5": {
         "description": "Demo 5",
         "objects": ["library", "hall", "lounge"],
         "preview_image": "./assets/scene_5.png",
+        "glb_path": "scene_assets/demo5_no_ceiling.glb",
         "default_instruction": "Walk straight through the double wood doors, follow the red carpet straight to the next doorway and stop where the carpet splits off."
     },
 }
 
+EPISODE_CONFIGS = {
+    "episode_1": {
+        "description": "1",
+    },
+    "episode_2": {
+        "description": "2",
+    },
+    "episode_3": {
+        "description": "3",
+    },
+    "episode_4": {
+        "description": "4",
+    }
+}
+
 MODEL_CHOICES = ["rdp", "cma"]
 MODE_CHOICES = ["vlnPE", "vlnCE"]

navigation_ui.py

@@ -0,0 +1,575 @@
+import base64
+import json
+import logging
+import os
+import subprocess
+import sys
+import threading
+import time
+import uuid
+from datetime import datetime, timedelta
+from typing import Dict, List, Optional
+
+import gradio as gr
+import numpy as np
+import open3d as o3d
+import plotly.graph_objects as go
+import requests
+from fastapi import APIRouter, FastAPI, HTTPException, status, BackgroundTasks, Response
+from pydantic import BaseModel
+
+import asyncio
+import uvicorn
+from collections import defaultdict
+
+BACKEND_URL = os.getenv("BACKEND_URL", "http://localhost:8001") # fastapi server
+API_ENDPOINTS = {
+    "submit_task": f"{BACKEND_URL}/predict/video",
+    "query_status": f"{BACKEND_URL}/predict/task",
+    "get_result": f"{BACKEND_URL}/predict"
+}
+
+
+SCENE_CONFIGS = {
+    "scene_1": {
+        "description": "Modern Apartment",
+        "name": "17DRP5sb8fy",
+        "glb_path": "scene_assets/scene1_no_ceiling.glb"  # PLY file path
+    },
+    "scene_2": {
+        "description": "Office Building",
+        "name": "r1Q1Z4BcV1o",
+        "glb_path": "scene_assets/scene2_no_ceiling.glb"
+    },
+    "scene_3": {
+        "description": "University Campus",
+        "name": "dhjEzFoUFzH",
+        "glb_path": "scene_assets/scene3_no_ceiling.glb"
+    },
+}
+
+EPISODE_CONFIGS = {
+    "episode_1": {
+        "description": "1",
+    },
+    "episode_2": {
+        "description": "2",
+    },
+    "episode_3": {
+        "description": "3",
+    },
+    "episode_4": {
+        "description": "4",
+    }
+}
+
+MODEL_CHOICES = [] 
+
+
+###############################################################################
+
+SESSION_TASKS = {}
+IP_REQUEST_RECORDS = defaultdict(list)
+IP_LIMIT = 5  
+
+def is_request_allowed(ip: str) -> bool:
+    now = datetime.now()
+    IP_REQUEST_RECORDS[ip] = [t for t in IP_REQUEST_RECORDS[ip] if now - t < timedelta(minutes=1)]
+    if len(IP_REQUEST_RECORDS[ip]) < IP_LIMIT:
+        IP_REQUEST_RECORDS[ip].append(now)
+        return True
+    return False
+
+###############################################################################
+
+
+# Log directory path
+LOG_DIR = "~/logs"
+os.makedirs(LOG_DIR, exist_ok=True)
+ACCESS_LOG = os.path.join(LOG_DIR, "access.log")
+SUBMISSION_LOG = os.path.join(LOG_DIR, "submissions.log")
+
+def log_access(user_ip: str = None, user_agent: str = None):
+    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    log_entry = {
+        "timestamp": timestamp,
+        "type": "access",
+        "user_ip": user_ip or "unknown",
+        "user_agent": user_agent or "unknown"
+    }
+    
+    with open(ACCESS_LOG, "a") as f:
+        f.write(json.dumps(log_entry) + "\n")
+
+def log_submission(scene: str, prompt: str, model: str, user: str = "anonymous", res: str = "unknown"):
+    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    log_entry = {
+        "timestamp": timestamp,
+        "type": "submission",
+        "user": user,
+        "scene": scene,
+        "prompt": prompt,
+        "model": model,
+        #"max_step": str(max_step),
+        "res": res
+    }
+    
+    with open(SUBMISSION_LOG, "a") as f:
+        f.write(json.dumps(log_entry) + "\n")
+
+def read_logs(log_type: str = "all", max_entries: int = 50) -> list:
+    logs = []
+    
+    if log_type in ["all", "access"]:
+        try:
+            with open(ACCESS_LOG, "r") as f:
+                for line in f:
+                    logs.append(json.loads(line.strip()))
+        except FileNotFoundError:
+            pass
+    
+    if log_type in ["all", "submission"]:
+        try:
+            with open(SUBMISSION_LOG, "r") as f:
+                for line in f:
+                    logs.append(json.loads(line.strip()))
+        except FileNotFoundError:
+            pass
+    
+    # Sorted by timestemp
+    logs.sort(key=lambda x: x["timestamp"], reverse=True)
+    return logs[:max_entries]
+
+def format_logs_for_display(logs: list) -> str:
+    if not logs:
+        return "No log record"
+    
+    markdown = "### System Access Log\n\n"
+    markdown += "| Time | Type | User/IP | Details |\n"
+    markdown += "|------|------|---------|----------|\n"
+    
+    for log in logs:
+        timestamp = log.get("timestamp", "unknown")
+        log_type = "Access" if log.get("type") == "access" else "Submission"
+        
+        if log_type == "Access":
+            user = log.get("user_ip", "unknown")
+            details = f"User-Agent: {log.get('user_agent', 'unknown')}"
+        else:
+            user = log.get("user", "anonymous")
+            result = log.get('res', 'unknown')
+            if result != "success": 
+                if len(result) > 40:  # Adjust this threshold as needed
+                    result = f"{result[:20]}...{result[-20:]}"
+            details = f"Scene: {log.get('scene', 'unknown')}, Prompt: {log.get('prompt', '')}, Model: {log.get('model', 'unknown')}, result: {result}"
+        
+        markdown += f"| {timestamp} | {log_type} | {user} | {details} |\n"
+    
+    return markdown
+
+
+def submit_to_backend(
+    scene: str,
+    prompt: str,
+    episode: str,
+    user: str = "Gradio-user",
+) -> dict:
+    job_id = str(uuid.uuid4())
+
+    scene_index = scene.split("_")[-1]
+    episode_index = episode.split("_")[-1]
+
+    data = {
+        "task_type": "vln_eval",  # Identify task type
+        "instruction": prompt,
+        "scene_index": scene_index,
+        "episode_index": episode_index,
+    }
+    
+    payload = {
+        "user": user,
+        "task": "robot_navigation",
+        "job_id": job_id,
+        "data": json.dumps(data)
+    }
+    
+    try:
+        headers = {"Content-Type": "application/json"}
+        response = requests.post(
+            API_ENDPOINTS["submit_task"],
+            json=payload,
+            headers=headers,
+            timeout=600
+        )
+        return response.json()
+    except Exception as e:
+        return {"status": "error", "message": str(e)}
+
+def get_task_status(task_id: str) -> dict:
+    try:
+        response = requests.get(f"{API_ENDPOINTS['query_status']}/{task_id}", timeout=600)
+        try:
+            return response.json()  
+        except json.JSONDecodeError:
+            return {"status": "error", "message": response.text}
+    except Exception as e:
+        return {"status": "error", "message": str(e)}
+
+
+def get_task_result(task_id: str) -> Optional[dict]:
+    try:
+        response = requests.get(
+            f"{API_ENDPOINTS['get_result']}/{task_id}",
+            timeout=5
+        )
+        return response.json()
+    except Exception as e:
+        print(f"Error fetching result: {e}")
+        return None
+
+def run_simulation(
+    scene: str,
+    prompt: str,
+    episode: str,
+    history: list,
+    request: gr.Request
+) -> dict:
+    model = "InternNav-VLA"
+
+    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    scene_desc = SCENE_CONFIGS.get(scene, {}).get("description", scene)
+
+    user_ip = request.client.host if request else "unknown"
+    session_id = request.session_hash
+
+    if not is_request_allowed(user_ip):
+        log_submission(scene, prompt, model, user_ip, "IP blocked temporarily")
+        raise gr.Error("Too many requests from this IP. Please wait and try again one minute later.")
+    
+    submission_result = submit_to_backend(scene, prompt, episode)
+    print("submission_result: ", submission_result)
+
+    if submission_result.get("status") != "pending":
+        log_submission(scene, prompt, model, user_ip, "Submission failed")
+        raise gr.Error(f"Submission failed: {submission_result.get('message', 'unknown issue')}")
+    
+    try:
+        task_id = submission_result["task_id"]
+        SESSION_TASKS[session_id] = task_id
+
+        gr.Info(f"Simulation started, task_id: {task_id}")
+        time.sleep(5)
+        # Get Task Status
+        status = get_task_status(task_id)
+        print("first status: ", status)
+        result_folder = status.get("result", "")
+    except Exception as e:
+        log_submission(scene, prompt, model, user_ip, str(e))
+        raise gr.Error(f"error occurred when parsing submission result from backend: {str(e)}")
+
+    while True:
+        status = get_task_status(task_id)
+        if status.get("status") == "completed":
+            break
+        elif status.get("status") == "failed":
+            break
+        time.sleep(1)
+    if status.get("status") == "completed":
+        import base64
+        video_bytes = base64.b64decode(status.get("video"))
+        receive_time = time.time()
+        with open(f"received_video_{receive_time}.mp4", "wb") as f:
+            f.write(video_bytes)
+        video_path = f"received_video_{receive_time}.mp4"
+        new_entry = {
+            "timestamp": timestamp,
+            "scene": scene,
+            "model": model,
+            "prompt": prompt,
+            "video_path": video_path
+        }
+        
+        updated_history = history + [new_entry]
+        
+        if len(updated_history) > 10:
+            updated_history = updated_history[:10]
+        
+        print("updated_history:", updated_history)
+        log_submission(scene, prompt, model, user_ip, "success")
+        gr.Info("Simulation completed successfully!")
+        yield video_path, updated_history
+
+    elif status.get("status") == "failed":
+        log_submission(scene, prompt, model, user_ip, status.get('result', 'backend error'))
+        raise gr.Error(f"task execution fails: {status.get('result', 'backend error')}")
+        yield None, history
+
+    elif status.get("status") == "terminated":
+        log_submission(scene, prompt, model, user_ip, "terminated")
+        video_path = os.path.join(result_folder, "output.mp4")
+        if os.path.exists(video_path):
+            return f" task {task_id} terminated with some results", video_path, history
+        else:
+            return f" task {task_id} terminated without any results", None, history
+
+    else:
+        log_submission(scene, prompt, model, user_ip, "missing task's status from backend")
+        yield None, history
+
+###################################################################################################################
+def update_history_display(history: list) -> list:
+    print("update_history_display")
+    updates = []
+    
+    for i in range(10):
+        if i < len(history):
+            entry = history[i]
+            updates.extend([
+                gr.update(visible=True),
+                gr.update(visible=True, label=f"Simulation {i+1}  scene: {entry['scene']}, prompt: {entry['prompt']}", open=False),
+                gr.update(value=entry['video_path'], visible=True),
+                gr.update(value=f"{entry['timestamp']}")
+            ])
+            print(f'update video')
+            print(entry['video_path'])
+        else:
+            updates.extend([
+                gr.update(visible=False),
+                gr.update(visible=False),
+                gr.update(value=None, visible=False),
+                gr.update(value="")
+            ])
+    print("update_history_display end!!")
+    return updates
+
+def update_scene_display(scene: str):
+    print(f"update_scene_display {scene}")
+    config = SCENE_CONFIGS.get(scene, {})
+    glb_path = config.get("glb_path", "")
+
+    # Validate if file path exists
+    if not os.path.exists(glb_path):
+        return None, None
+
+    return None, glb_path
+
+def update_episode_display(scene: str, episode: str):
+    print(f"update_episode_display {scene} {episode}")
+    config = SCENE_CONFIGS.get(scene, {})
+    scene_name = config.get("name", "")
+    episode_id = int(episode[-1])
+    image_path = os.path.join("scene_assets", f"{scene_name}_{episode_id-1}.jpg")
+    print(f"image_path {image_path}")
+    # vaild if file path exists
+    if not os.path.exists(image_path):
+        return None
+
+    return image_path
+def update_log_display():
+    logs = read_logs()
+    return format_logs_for_display(logs)
+##############################################################################
+
+
+def cleanup_session(request: gr.Request):
+    session_id = request.session_hash
+    task_id = SESSION_TASKS.pop(session_id, None)
+    if task_id:
+        try:
+            requests.post(f"{BACKEND_URL}/predict/terminate/{task_id}", timeout=3)
+            print(f"Task Terminated: {task_id}")
+        except Exception as e:
+            print(f"Task Termination Failed: {task_id}: {e}")
+
+
+
+###############################################################################
+
+custom_css = """
+#simulation-panel {
+    border-radius: 8px;
+    padding: 20px;
+    background: #f9f9f9;
+    box-shadow: 0 2px 4px rgba(0,0,0,0.1);
+}
+#result-panel {
+    border-radius: 8px;
+    padding: 20px;
+    background: #f0f8ff;
+}
+.dark #simulation-panel { background: #2a2a2a; }
+.dark #result-panel { background: #1a2a3a; }
+
+.history-container {
+    max-height: 600px;
+    overflow-y: auto;
+    margin-top: 20px;
+}
+
+.history-accordion {
+    margin-bottom: 10px;
+}
+
+.scene-preview {
+    height: 400px;
+    border: 1px solid #ddd;
+    border-radius: 8px;
+    overflow: hidden;
+}
+"""
+
+with gr.Blocks(title="Robot Navigation Inference", css=custom_css) as demo:
+    gr.Markdown("""
+    # 🧭 Habitat Robot Navigation Demo
+    ### Simulation Test Based on Habitat Framework
+    """)
+    
+    history_state = gr.State([])
+
+    with gr.Row():
+        with gr.Column(elem_id="simulation-panel"):
+            gr.Markdown("### Simulation Task Configuration")
+            with gr.Row():
+                scene_dropdown = gr.Dropdown(
+                    label="Select Scene",
+                    choices=list(SCENE_CONFIGS.keys()),
+                    value="scene_1",
+                    interactive=True,
+            )
+                episode_dropdown = gr.Dropdown(
+                    label="Select Start Position",
+                    choices=list(EPISODE_CONFIGS.keys()),
+                    value="episode_1",
+                    interactive=True,
+                )
+
+            with gr.Row():
+                scene_preview = gr.Model3D(elem_classes=["scene-preview"],
+                camera_position=(90.0, 120, 20000.0),
+                #display_mode="solid"
+                )
+                fps_preview = gr.Image(label="FPS Preview")
+            
+            scene_description = gr.Markdown("### Scene preview")
+            
+            prompt_input = gr.Textbox(
+                label="Navigation Instruction",
+                value="Exit the bedroom and turn left. Walk straight passing the gray couch and stop near the rug.",
+                placeholder="e.g.: 'Exit the bedroom and turn left. Walk straight passing the gray couch and stop near the rug.'",
+                lines=2,
+                max_lines=4
+            )
+                        
+            scene_dropdown.change(
+                update_scene_display,
+                inputs=scene_dropdown,
+                outputs=[scene_description, scene_preview]
+            ).then(
+                update_episode_display,
+                inputs=[scene_dropdown, episode_dropdown],
+                outputs=[fps_preview]
+            )
+            
+            episode_dropdown.change(
+                update_episode_display,
+                inputs=[scene_dropdown, episode_dropdown],
+                outputs=[fps_preview]
+            )
+            
+            submit_btn = gr.Button("Start Navigation Simulation", variant="primary")
+
+       
+        with gr.Column(elem_id="result-panel"):
+            gr.Markdown("### Latest Simulation Result")
+
+            # Video Output
+            video_output = gr.Video(
+                label="Live",
+                interactive=False,
+                format="mp4",
+                autoplay=True,
+                # streaming=True
+            )
+            
+            with gr.Column() as history_container:
+                gr.Markdown("### History")
+                gr.Markdown("#### History will be reset after refresh")
+                
+                history_slots = []
+                for i in range(10):
+                    with gr.Column(visible=False) as slot:
+                        with gr.Accordion(visible=False, open=False) as accordion:
+                            video = gr.Video(interactive=False)  
+                            detail_md = gr.Markdown() 
+                    history_slots.append((slot, accordion, video, detail_md))  
+    
+    with gr.Accordion("View System Log (DEV ONLY)", open=False):
+        logs_display = gr.Markdown()
+        refresh_logs_btn = gr.Button("Refresh Log", variant="secondary")
+        
+        refresh_logs_btn.click(
+            update_log_display,
+            outputs=logs_display
+        )
+
+    gr.Examples(
+        examples=[
+            ["scene_1", "Exit the bedroom and turn left. Walk straight passing the gray couch and stop near the rug.", "episode_0"],
+            ["scene_2", "Go from reception to conference room passing the water cooler.", "episode_1"],
+            ["scene_3", "From the classroom, go to the library via the main hall.", "episode_2"],
+            ["scene_4", "From emergency room to pharmacy passing nurse station.", "episode_3"]
+        ],
+        inputs=[scene_dropdown, prompt_input, episode_dropdown],
+        label="Navigation Task Example"
+    )
+    
+    submit_btn.click(
+        fn=run_simulation,
+        inputs=[scene_dropdown, prompt_input, episode_dropdown, history_state],
+        outputs=[video_output, history_state],
+        queue=True,
+        api_name="run_simulation"
+    ).then(
+        fn=update_history_display,
+        inputs=history_state,
+        outputs=[comp for slot in history_slots for comp in slot],
+        queue=True
+    ).then(
+        fn=update_log_display,
+        outputs=logs_display,
+    )
+
+
+    demo.load(
+        fn=lambda: update_scene_display("scene_1"),
+        outputs=[scene_description, scene_preview]
+    ).then(
+        fn=update_log_display,
+        outputs=logs_display
+    )
+    demo.load(
+        fn=lambda: update_episode_display("scene_1", "episode_1"),
+        outputs=[fps_preview]
+    )
+
+    def record_access(request: gr.Request):
+        user_ip = request.client.host if request else "unknown"
+        user_agent = request.headers.get("user-agent", "unknown")
+        log_access(user_ip, user_agent)
+        return update_log_display()   
+
+    demo.load(
+        fn=record_access,
+        inputs=None,
+        outputs=logs_display,
+        queue=False
+    )
+
+    demo.queue(default_concurrency_limit=8)
+
+    demo.unload(fn=cleanup_session)
+
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0", server_port=5750, debug=True, share = True, allowed_paths=["/mnt"])
+
+    

ui_components.py

@@ -1,7 +1,8 @@
 # ui_components.py
 # Gradio界面相关和辅助函数
 import gradio as gr
-from config import SCENE_CONFIGS
+import os
+from config import SCENE_CONFIGS, EPISODE_CONFIGS
 from logging_utils import read_logs, format_logs_for_display
 
 def update_history_display(history: list) -> list:
@@ -29,9 +30,26 @@ def update_scene_display(scene: str):
     config = SCENE_CONFIGS.get(scene, {})
     desc = config.get("description", "No Description")
     objects = "、".join(config.get("objects", []))
-    image = config.get("preview_image", None)
+    glb_path = config.get("glb_path", "")
     markdown = f"**{desc}**  \nPlaces Included: {objects}"
-    return markdown, image
+    
+    # Validate if file path exists
+    if not os.path.exists(glb_path):
+        return markdown, None
+    
+    return markdown, glb_path
+
+def update_episode_display(scene: str, episode: str):
+    config = SCENE_CONFIGS.get(scene, {})
+    scene_name = scene  # 使用demo1, demo2等作为scene_name
+    episode_id = int(episode[-1])
+    image_path = os.path.join("scene_assets", f"{scene_name}_{episode_id-1}.jpg")
+    
+    # Validate if file path exists
+    if not os.path.exists(image_path):
+        return None
+    
+    return image_path
 
 def get_scene_instruction(scene: str):
     """根据场景获取默认指令"""